A new adaptive algorithm to reduce weight fluctuations caused by high variance data

A nongradient iterative algorithm that has reduced adaptive filter weight fluctuations caused by high variance input data is presented. The algorithm adapts a single weight at each time step and has approximately the same computational requirements as the LMS algorithm.< >

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on signal processing 1992-09, Vol.40 (9), p.2324-2327
Hauptverfasser:	Cilke, J.T., Etter, D.M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive algorithm Adaptive filters Convergence Equations Finite impulse response filter Fluctuations Gaussian processes Noise cancellation Predictive models Signal processing algorithms
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